Increase In PM2 Research Articles

Coordinating public and government responses to air pollution exposure: A multi-source data fusion approach

Aligning public demand with government supply of clean air aids in efficient air pollution control and enhancement of public happiness. However, comparative empirical analyses of public and government attention to air quality changes are still sparse due to data and methodological constraints. Here, we adopt multi-source data fusion approaches to assess the impacts of air pollution exposure on public and government attention. Specifically, remote and social sensing data, alongside keywords extracted from textual data, are utilized to quantify air pollution exposure and corresponding public and government attention levels in 273 Chinese cities from 2011 to 2019, and a two-stage least squares regression model is employed to tackle reverse causality issues underlying the exposure-response relationship. Our findings reveal that, on average, a unit increase in PM2.5 levels would result in a 17.7% growth in public attention and a 12.7% rise in government attention, respectively, suggesting that demand-driven public attention tends to be more sensitive to air quality changes than policy-driven government attention. Results for the spatial-temporal heterogeneity further demonstrate that public attention varies across time and space, whereas government attention remains relatively consistent. Additionally, we have identified 116 cities exhibiting disparities between the public and government responses to air quality changes, calling for environmental policy refinements to better serve the needs of residents. This study emphasizes the necessity of public engagement in environmental governance and offers rich policy implications for air pollution control in China.

Long-term exposure to fine particulate matter constituents, genetic susceptibility, and incident heart failure among 411 807 adults.

Long-term fine particulate matter (PM2.5) exposure has been linked to incident heart failure (HF), but the impacts of its constituents remain unknown. We aimed to investigate the associations of PM2.5 constituents with incident HF, and further evaluate the modification effects of genetic susceptibility. PM2.5 and its constituents, including elemental carbon (EC), organic matter (OM), ammonium (NH4 +), nitrate (NO3 -), and sulfate (SO4 2-), were estimated using the European Monitoring and Evaluation Programme model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology. A polygenic risk score (PRS) was calculated to represent genetic susceptibility to HF. We employed Cox models to evaluate the associations of PM2.5 constituents with incident HF. Quantile-based g-computation model was used to identify the main contributor of PM2.5 constituents. Among 411 807 individuals in the UK Biobank, 7554 participants developed HF during a median follow-up of 12.05 years. The adjusted hazard ratios of HF for each interquartile range increase in PM2.5, EC, OM, NH4 +, NO3 -, and SO4 2- were 1.50 (1.46-1.54), 1.31 (1.27-1.34), 1.12 (1.09-1.15), 1.42 (1.41-1.44), 1.26 (1.23-1.29), and 1.25 (1.24-1.26), respectively. EC (43%) played the most important role, followed by NH4 + and SO4 2-. Moreover, synergistic additive interactions accounted for 9-16% of the HF events in individuals exposed to both PM2.5, NH4 +, NO3 -, and SO4 2- and PRS. Long-term exposure to PM2.5 constituents may elevate HF risk, and EC was the major contributor. Additive effects of PM2.5 constituents and PRS on HF risk were revealed.

PM2.5 Exposure as a Risk Factor for Optic Nerve Health in Type 2 Diabetes Mellitus

(1) Objective: This study investigated the relationship between long-term particulate matter (PM2.5) exposure and optic disc parameters—vertical cup-to-disc ratio (vCDR), vertical optic disc diameter (vDD), and vertical optic cup diameter (vCD)—in patients with type 2 diabetes mellitus (T2DM). (2) Methods: A cross-sectional analysis was conducted using data from 65,750 T2DM patients in the 2017–2018 Shanghai Cohort Study of Diabetic Eye Disease (SCODE). Optic disc parameters were extracted from fundus images, and PM2.5 exposure was estimated using a random forest model incorporating satellite and meteorological data. Multivariate linear regression models were applied, adjusting for confounders including age, gender, body mass index, blood pressure, glucose, time of T2DM duration, smoking, drinking, and physical exercise. (3) Results: A 10 μg/m3 increase in PM2.5 exposure was associated with significant reductions in vCDR (−0.008), vDD (−42.547 μm), and vCD (−30.517 μm) (all p-values < 0.001). These associations persisted after sensitivity analyses and adjustments for other pollutants like O3 and NO2. (4) Conclusions: Long-term PM2.5 exposure is associated with detrimental changes in optic disc parameters in patients with T2DM, suggesting possible optic nerve atrophy. Considering the close relationship between the optic nerve and the central nervous system, these findings may also reflect broader neurodegenerative processes.

Wildfire Seasons, Prenatal PM2.5 Exposure, and Respiratory Infections by Age 1 Year: A Population-Based Case-Control Analysis of Critical Developmental Windows.

The 2017 and 2018 wildfire seasons in British Columbia (BC), Canada were unprecedented. Among all the pollutants in wildfire smoke, fine particulate matter (PM2.5) poses the most significant risk to human health. There is limited research on prenatal wildfire smoke exposure and its impacts on infant health. We used a population-based nested case-control design to assess the association between daily PM2.5 exposures during specific developmental windows and the occurrence of otitis media or lower respiratory infections by age 1 year, including infections associated with dispensations of the antibiotic amoxicillin. We observed the strongest association between per 10 μg/m3 increase in PM2.5 exposure and otitis media during the fourth window of eustachian tube development (weeks 19-28) with an OR [95% confidence interval] of 1.31 [1.22, 1.41]. Similarly, the canalicular stage of lower respiratory tract development (weeks 18-27) was associated with the highest odds of lower respiratory infections, with an OR of 1.21 [1.15, 1.28]. Measures to reduce wildfire smoke exposure during pregnancy are warranted.

Association of Ambient Air Pollution Exposure With Incident Glaucoma: 12-Year Evidence From the UK Biobank Cohort.

Glaucoma is the leading cause of irreversible blindness worldwide. Despite growing concerns about air quality and its impact on ocular health, there remains a knowledge gap regarding the long-term association between air pollution and glaucoma risk. This study investigates the relationship between exposure to ambient air pollution and incidence of glaucoma. In this prospective study, we used land use regression models to estimate levels of various air pollutants, including fine particulate matter (PM2.5), PM2.5 absorbance, PM2.5-10, PM10, nitrogen dioxide (NO2), and nitrogen oxides (NOx). Incidents of glaucoma were ascertained through routinely collected hospital admission records. Multivariate Cox proportional hazards models were used to examine the associations between air pollution exposure and glaucoma incidence, adjusting for potential confounding sociodemographic, physical, and lifestyle factors. Data from 481,113 participants were included. Over a median follow-up of 12.8 years, 9224 incident cases of glaucoma were identified. In the maximally adjusted model, per interquartile range increase in PM2.5 was associated with a 3% greater risk of developing glaucoma (hazard ratio [HR] = 1.03, 95% confidence interval [CI] = 1.00 to 1.06, P = 0.048). Participants in the highest quartile had a 10% increased risk of developing glaucoma compared to those in the lowest quartile (HR = 1.10, 95% CI = 1.03 to 1.17, P = 0.005). Higher levels of exposure to ambient air pollutants, particularly PM2.5, are associated with an increased risk of developing glaucoma. These results highlight the potential public health impact of ambient air pollution on glaucoma risk and underscore the urgent need for further research into targeted environmental interventions in this domain.

Effect of air pollution, genetic susceptibility on the risk of all-cause mortality and cardiovascular outcomes among atrial fibrillation patients

Objective: To analyze the association between air pollution, genetic susceptibility, and the risk of all-cause mortality and cardiovascular outcomes in patients with atrial fibrillation (AF). Methods: AF patients aged between 40-69 years old registered in the United Kingdom Biobank from 2006 to 2010 were included. After excluding those lost to follow-up or with incomplete data during follow-up, 5 814 subjects were analyzed. Long-term exposure to air pollution was estimated at the geocoded residential address of each participant. Genetic risk scores for all-cause mortality, cardiovascular disease, heart failure, myocardial infarction, and stroke were constructed separately for each object to assess the corresponding genetic susceptibility. The Cox proportional hazards model was used to analyze the association between air pollution, genetic susceptibility, and the risk of all-cause mortality and cardiovascular outcomes in AF patients. Results: During a median follow-up of 12.4 years, there were 929 of all-cause mortality (15.98%) and 1 772 of cardiovascular events (30.48%). Multivariable-adjusted analyses revealed that higher exposure to PM2.5, PM10, NOx, and NO2 was associated with an increased risk of cardiovascular disease mortality, heart failure, myocardial infarction, and stroke, with hazard ratios (HRs) ranging from 1.26 to 1.48. Specifically, for each interquartile range (IQR) increase in PM2.5 exposure, the HRs for the outcomes mentioned above were 1.33 (95%CI: 1.14-1.54), 1.42 (95%CI: 1.31-1.54), 1.46 (95%CI: 1.30-1.64), and 1.43 (95%CI: 1.27-1.61), respectively. Both NOx and NO2 exposures were associated with a 9% increased risk of all-cause mortality per IQR increment, with corresponding HRs of 1.09 (95%CI: 1.02-1.17) and 1.09 (95%CI: 1.01-1.17), respectively. Individuals with high genetic susceptibility to AF had a higher risk of myocardial infarction and stroke compared to those with low genetic susceptibility, with corresponding HRs of 1.39 (95%CI: 1.04-1.87) and 1.46 (95%CI: 1.09-1.95), respectively. Compared to AF patients with low air pollution exposure, those with high air pollution exposure have adjusted population attributable fractions of up to 33.57% (95%CI: 17.87%-46.26%) for cardiovascular mortality, 28.61% (95%CI: 20.67%-35.75%) for heart failure, 33.35% (95%CI: 20.97%-43.79%) for myocardial infarction, and 42.29% (95%CI: 30.05%-52.71%) for stroke. Furthermore, there was an additive interaction between PM2.5, NOx, and NO2 exposure and high genetic susceptibility on the incidence of myocardial infarction. An additive interaction was also observed between NOx, NO2 exposure, and high genetic susceptibility on the incidence of heart failure (all P<0.05). Conclusions: Both air pollution and genetic susceptibility increase the risk of all-cause mortality and cardiovascular outcomes in AF patients.

Air pollution exposure during pregnancy and preterm birth in Brazil

Ambient air pollution is a significant environmental risk factor for adverse pregnancy outcomes, including preterm birth. However, the impact of different pollutants across various regions and trimesters of pregnancy has not been fully investigated in Brazil. This study aimed to examine the associations between exposure to PM2.5, NO2, and O3 during different trimesters of pregnancy and the risk of preterm birth across five regions of Brazil. We used logistic regression models to estimate the odds ratios (OR) of preterm birth associated with PM2.5, NO2, and O3 adjusting for potential confounders such as maternal age, education, and socioeconomic status. Our study included over 9.9 million live births from 2001 to 2018, with data obtained from the Ministry of Health in Brazil. On average, for each 1-μg/m3 increase in PM2.5, we estimated a 0.26 % (95 % CI: 0.08–0.44 %) increase in the risk of preterm birth nationally in the first trimester. For NO2, each 1ppb increase was associated with a percentage increase in preterm birth risk of 7.26 % (95 % CI: 4.77–9.74 %) in the first trimester, 8.05 % (95 % CI: 5.73–10.38 %) in the second trimester, and 7.48 % (95 % CI: 5.25–9.72 %) in the third trimester. For O3, each 1ppb increase was associated with a percentage increase in preterm birth risk of 1.24 % (95 % CI: 0.29–2.18 %) in the first trimester, 1.51 % (95 % CI: 0.60–2.41 %) in the second trimester, and 0.72 % (95 % CI: −0.18–1.62 %) in the third trimester. This study highlights the significant impact of ambient air pollution on preterm birth risk in Brazil, with significant regional variations. Our findings underscore the need for targeted public health interventions to mitigate the effects of air pollution on pregnancy outcomes, particularly in the most affected regions.

Effects of outdoor air pollution on hospital admissions from cardiovascular diseases in the capital city of Mongolia

Cardiovascular diseases (CVD) are one of the primary causes of morbidity worldwide, while ambient air pollution (AAP) is a major contributor to CVD. This study is the first study that aimed to compare the differences in AAP concentrations and acute effects on the risk of admissions from CVD, ischaemic heart diseases (IHD), and stroke before and after introducing the new type of coal briquette in Ulaanbaatar, Mongolia. We collected daily hospital admission records, air quality and meteorology data between January 1, 2016 and December 31, 2022. The relative risks (RRs) of cause-specific hospitalisations associated with daily concentrations of AAP were estimated by a time-stratified case-crossover analysis with conditional Poisson distributed lag models. Overall, acute exposure to the pollutants, except for O3, was positively associated with an increased risk of all admissions. For each interquartile range (IQR) increase in PM2.5, PM10, SO2, NO2 and CO, the risk of CVD admissions increased by 0.5% (RR=1.005; 95% CI: 0.998, 1.012) at lag0, 2.9% (RR=1.029; 95% CI: 1.014, 1.044), 2.5% (RR=1.025; 95% CI: 1.010, 1.040), 4.1% (RR=1.041; 95% CI: 1.016, 1.068) and 0.3% (RR=1.003; 95% CI: 0.995, 1.012) at lag01, respectively. Subgroup analyses showed greater risks of CVD admissions for women and people aged <65 years, in the cold season, and after the raw coal ban period. During the cold winter season, Ulaanbaatar’s AAP levels remained higher than the World Health Organization’s guidelines, regardless of consuming the new coal briquettes. Adopting alternative efficient methods to improve air quality and associated health outcomes is necessary.

Long-term exposure to ambient air pollution and risk of lung cancer – A comparative analysis of incidence and mortality in four administrative cohorts in the ELAPSE study

BackgroundStudies have linked air pollution to lung cancer incidence and mortality, but few have compared these associations, which may differ due to cancer survival variations. We aimed to evaluate the association between long-term air pollution exposure and lung cancer incidence and compare findings with previous lung cancer mortality analyses within the same cohorts. MethodsWe analyzed four population-based administrative cohorts in Denmark (2000–2015), England (2011–2017), Norway (2001–2016) and Rome (2001–2015). We assessed residential exposure to annual average fine particulate matter (PM2.5), nitrogen dioxide (NO₂), black carbon (BC), and warm-season ozone (O3) using Europe-wide land use regression models. We used Cox proportional hazard models to evaluate cohort-specific hazard ratios (HRs) and 95% confidence intervals (CIs) for lung cancer incidence identified using hospital admission records (English and Roman cohorts) or cancer registries (Danish and Norwegian cohorts). We evaluated the associations at low exposure levels using subset analyses and natural cubic splines. Cohort-specific HRs were pooled using random-effects meta-analyses, separately for incidence and mortality. ResultsOver 93,733,929 person-years of follow-up, 111,949 incident lung cancer cases occurred. Incident lung cancer was positively associated with PM2.5, NO2 and BC, and negatively associated with O3. The negative O3 association became positive after adjustment for NO2. Associations were almost identical or slightly stronger for lung cancer incidence than mortality in the same cohorts, with respective meta-analytic HRs (95% CIs) of 1.14 (1.06, 1.22) and 1.12 (1.02, 1.22) per 5 μg/m3 increase in PM2.5, and 1.10 (1.04, 1.16) and 1.09 (1.02, 1.16) per 10 μg/m3 increase in NO2. Positive associations persisted for both incidence and mortality at low pollution levels with similar magnitude. ConclusionsWe found similarly elevated risks of lung cancer incidence and mortality in association with residential exposure to PM2.5, NO2 and BC in meta-analyses of four European administrative cohorts, which persisted at low pollution levels.

Association of fine particulate matter and residential green space with rheumatoid arthritis

BackgroundFine particulate matter (PM2.5) is a recognized risk factor for respiratory and cardiovascular diseases, but the association between PM2.5 and rheumatoid arthritis (RA) is still controversial. Additionally, evidence on the relationship of green space with RA is scarce. This study aimed to investigate the separate and combined associations of PM2.5 and green space with risk of RA. MethodsOur study involved 30,684 participants from the Yinzhou cohort in Ningbo, China. PM2.5 concentrations were determined using a land-use regression model. Residential green space was assessed using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from satellite images. We employed the Cox proportional hazard model to evaluate the relationships of PM2.5 and green space with RA. ResultsDuring the 176,894 person-years of follow-up period, 354 cases of RA were identified. Hazard ratio (HR) and the corresponding 95% confidence interval (95% CI) for every interquartile range (IQR) increase in PM2.5 were 1.23 (95% CI: 1.02, 1.49). Compared with lower exposure to residential green space, individuals living in areas with more green space had a decreased risk of RA (HR was 0.80 (95% CI: 0.70, 0.92), 0.80 (95% CI: 0.70, 0.92), and 0.79 (95% CI: 0.70, 0.89) for 250m, 500m, and 1000m NDVI buffers, respectively). Similar results were observed for the association between EVI and RA. Furthermore, a significant multiplicative interaction was observed between PM2.5 and green space (NDVI 250m and EVI 250m). No mediating effect of PM2.5 on the relationship between green space and RA was observed. ConclusionOur findings indicated that living in areas with higher green space was linked to a reduced risk of RA, whereas living in areas with higher PM2.5 was associated with an increased risk of RA. The beneficial effect of high green space may be offset by exposure to PM2.5.

Short-term exposure to ambient air pollution and severe COVID-19: mortality and hospital admission to COVID-19 in the Netherlands from february to december 2020

This study aimed to examine acute effects of exposure to ambient air pollution on COVID-19 hospital admissions and mortality in the Netherlands. We hypothesized that exposure to increased air pollution in the preceding week might trigger an exacerbation of health of infected individuals.Associations between daily concentrations of particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) and ≤10 µm (PM10), nitrogen dioxide (NO2), ozone (O3) and risk of hospital admissions and mortality due to COVID-19 from February to December 2020 was analyzed across all 352 Dutch municipalities grouped into 12 provinces. Time-series models were used to fit province-specific estimates, followed by meta-analyses to produce national estimates. Analyses were based on daily averages of PM2.5, PM10, NO2, and maximum 8-hour running average of O3 on a 1×1 km grid and averaged on municipality level by population weight. Models were adjusted for spatiotemporal confounders, including government policies in response to the number of COVID-19 infections. Since there were only few COVID-19 cases during the summertime when O3 levels were highest, associations between O3 and COVID-19 health outcomes were not further explored.We found associations between exposure to air pollution in the preceding week (average of lag 0-7 days) and COVID-19 hospital admissions and mortality. On a national level, an interquartile range increase in PM2.5, PM10 and NO2 exposure was associated with 11-12% increased mortality risk; the risk for hospital admissions was higher: 19-25%. Observed associations were more robust for PM than NO2 in two-pollutant models.Our results suggest that short-term exposure to PM2.5 and PM10 may increase the risk of COVID-19 mortality and hospital admission. This indicates that, consistent with previous studies on air pollution and respiratory infections, the population at risk of being hospitalized or dying of COVID-19 is extra vulnerable to the adverse effects of short-term air pollution exposure.

Single- and two-pollutant Concentration-Response Functions for PM2.5 and NO2 for Quantifying Mortality Burden in Health Impact Assessments

ObjectiveHealth Impact Assessments (HIAs) for air pollutant mixtures are challenging because risk estimates are primarily derived from single-pollutant models. Combining risk estimates from multiple pollutants requires new approaches, as a simple addition of single pollutant risk estimates from correlated air pollutants may result in double counting. We investigated approaches applying concentration-response functions (CRFs) from single- and two-pollutant models in HIAs, focusing on long-term exposure to particulate matter with a diameter less than 2.5 micrometers (PM2.5) and nitrogen dioxide (NO2) and their associations with all-cause mortality. MethodsA systematic literature search of MEDLINE and EMBASE identified cohort studies employing single- and two-pollutant models of long-term exposure to PM2.5 and NO2 with all-cause mortality. Pooled CRFs were calculated through random-effects meta-analyses of risk estimates from single- and two-pollutant models. Coefficient differences were calculated by comparing single- and two-pollutant model estimates. Four approaches to estimating population-attributable fractions (PAFs) were compared: PM2.5 or NO2 single-pollutant models to represent the mixture, the sum of single-pollutant models, the sum of two-pollutant models and the sum of single-pollutant models from a larger body of evidence adjusted by coefficient difference. ResultsSeventeen papers reported both single and two-pollutant estimates. Pooled hazard ratios (HRs) for mortality from single- and two-pollutant models were 1.053 (95% confidence interval: 1.034-1.071) and 1.035 (1.014-1.057), respectively, for a 5 μg/m3 increase in PM2.5. HRs for a 10 μg/m3 increase in NO2 were 1.032 (1.014-1.049) and 1.024 (1.000-1.049) for single- and two-pollutant models, respectively. The average coefficient difference between single- and two-pollutant models was 0.017 for PM2.5 and 0.007 for NO2. Combined PAFs for the PM2.5-NO2 mixture using joint HRs from single- and two-pollutant model CRFs were 0.09 and 0.06, respectively. ConclusionUtilizing CRFs from two-pollutant models or applying the coefficient difference to a more extensive evidence base seems to mitigate the potential overestimation of mixture health impacts from adding single-pollutant CRFs.

The temporal trend and disparity in short-term health impacts of fine particulate matter in California (2006–2019)

Most epidemiological studies assume that the relationship between short-term air pollution exposure and health outcomes is constant over time, which ignores potential changes in population composition and particulate matter emission sources. Limited studies have assessed changes in the relationship between fine particulate matter (PM2.5) and adverse health outcomes over time, with mixed results. Additionally, there is a need to identify which subgroups are disproportionately impacted over time by PM2.5-related health consequences. Therefore, we aimed to examine whether temporal trends exist in the relationships between daily PM2.5 exposure and circulatory and respiratory acute care utilization in California from 2006 to 2019. We further assessed whether certain subpopulations are more susceptible to PM2.5 exposure by demographic characteristics and extreme wildfire frequency. Daily PM2.5 concentrations estimated from a stacked ensemble model and daily cause-specific acute care utilization and demographic data from the California Department of Health Care Access and Information. We analyzed this relationship using modified two-stage Bayesian hierarchical models, where we first did not consider temporal trends, then stratified by two periods, and finally flexibly considered non-linear changes over time. Increases in circulatory (0.56 %; 95 % credible interval (CI): 0.17 %, 0.96 %) and respiratory acute care utilization risk (2.61 %; 95%CI: 2.29 %, 2.94 %) were found with every 10 μg/m3 increase in PM2.5 on the same day and previous two days. These risks were found to increase over time, where 0.13 % (95%CI: 0.02 %, 0.22 %) and 1.40 % (95%CI: 1.24 %, 1.54 %) increases were identified for circulatory and respiratory acute care utilizations, respectively, from the first (2006–2012) to second period (2013–2019). Differences by age, sex, race/ethnicity, and extreme wildfire frequency were noted. These findings confirm that air pollution guidelines should consider the dynamic nature of epidemiological dose-response and can provide insight for targeted air pollution control and adaptation policies designed to reduce PM2.5 exposure, particularly for the most susceptible subpopulations.

Kidney Injury Evoked by Fine Particulate Matter: Risk Factor, Causation, Mechanism and Intervention Study.

Fine particulate matter (PM2.5) is suggested to pose a severe risk to the kidneys by inducing functional degradation and chronic kidney diseases (CKD). This study aims to explore the nephrotoxicity of PM2.5 exposure and the underlying mechanism. Herein, based on the UK Biobank, it is found that per interquartile range (IQR) increase in PM2.5 is associated with a 6% (95% CI: 1%-11%), 7% (95% CI: 3%-11%), 9% (95% CI: 4%-13%), 11% (95% CI: 9%-13%), and 10% (95% CI: 8%-12%) increase in the risk of nephritis, hydronephrosis, kidney stone, acute renal failure, and CKD, respectively. In experimental study, noticeable kidney injury, which is the initiation of kidney diseases, is observed with PM2.5 exposure in C57BL/6N mice (n = 8), accompanied with oxidative stress, autophagy and pyroptosis. In vitro, HK-2 cells with PM2.5-stimulation exhibit tubulopathy, increased reactive oxygen species (ROS) generation and activated pyroptosis and autophagy. All changes are abolished by ROS scavenger of N-acetyl-L-cysteine (NAC) both in vivo and in vitro. In conclusion, the study provides evidence showing that PM2.5 exposure is associated with 5 kinds of kidney diseases by directly inducing nephrotoxicity, in which ROS may be the potential target by triggering autophagy and pyroptosis.

Inequities in air pollution on stroke mortality among Older Americans: a U.S. nationwide analysis.

Air pollution is a known risk factor for cardiovascular diseases, including stroke. This study examines the impact of county-level air pollution on ischemic and hemorrhagic stroke mortality among U.S. individuals aged 65 and older, emphasizing racial and socioeconomic disparities. Using data from the Center for Disease Control (CDC) Interactive Atlas of Heart Disease and Stroke, we analyzed county-level ischemic stroke mortality rates for older residents between 2016 and 2020. The data on air pollution at the county level, specifically particulate matter (PM2.5) levels, were obtained from the CDC. We applied multivariable linear and logistic regression models to examine the association between PM2.5 levels and stroke mortality, as well as the probability of meeting the Environmental Protection Agency (EPA) air quality standards. County-level analysis revealed a significant correlation (R = 0.68, R2 = 0.48, p < 0.001) between PM2.5 levels and overall stroke mortality. For every 1 μg/m3 increase in PM2.5, there was an increase of 1.89 ischemic stroke deaths per 100,000 residents. Racial and socioeconomic disparities were evident. Counties with predominantly Black populations exhibited a stark disparity, with each 1 μg/m3 increase in PM2.5 correlating with a significant rise in mortality, amounting to 5.81 additional deaths per 100,000 residents. Persistently poor counties displayed vulnerability, experiencing a 4.05 increase in ischemic stroke deaths per 100,000 residents for every 1 μg/m3 increase in PM2.5 levels. Conversely, in counties with a White majority and counties without a persistent state of poverty, the associated increases in stroke mortality per 100,000 residents for every 1 μg/m3 rise in county-level PM2.5 were 1.85 and 1.60, respectively. Counties with a majority of Black residents were over twice as likely to be non-compliant with EPA air quality standards compared to predominantly White counties (aOR 2.36 95% CI: 1.27-4.38, p = 0.006). This study underscores the significant impact of county-level air pollution, particularly PM2.5, on ischemic stroke mortality among older U.S. residents. Our findings indicate that counties with predominantly Black populations and those experiencing persistent poverty not only suffer from higher mortality rates but also are more likely to be non-compliant with EPA air quality standards. Targeted interventions and policies are urgently needed to reduce air pollution in these vulnerable communities and promote equitable public health outcomes.

Multi-Scale Meteorological Impact on PM2.5 Pollution in Tangshan, Northern China.

Tangshan, a major industrial and agricultural center in northern China, frequently experiences significant PM2.5 pollution events during winter, impacting its large population. These pollution episodes are influenced by multi-scale meteorological processes, though the complex mechanisms remain not fully understood. This study integrates surface PM2.5 concentration data, ground-based and upper-air meteorological observations, and ERA5 reanalysis data from 2015 to 2019 to explore the interactions between local planetary boundary layer (PBL) structures and large-scale atmospheric processes driving PM2.5 pollution in Tangshan. The results indicate that seasonal variations in PM2.5 pollution levels are closely linked to changes in PBL thermal stability. During winter, day-to-day increases in PM2.5 concentrations are often tied to atmospheric warming above 1500 m, as enhanced thermal inversions and reduced PBL heights lead to pollutant accumulation. Regionally, this aloft warming is driven by a high-pressure system at 850 hPa over the southern North China Plain, accompanied by prevailing southwesterly winds. Additionally, southwesterly winds within the PBL can transport pollutants from the adjacent Beijing-Tianjin-Hebei region to Tangshan, worsening pollution. Simulations from the chemical transport model indicate that regional pollutant transport can contribute to approximately half of the near-surface PM2.5 concentration under the unfavorable synoptic conditions. These findings underscore the importance of multi-scale meteorology in predicting and mitigating severe wintertime PM2.5 pollution in Tangshan and surrounding regions.

The effect of air pollutants on COPD-hospitalized patients in Lanzhou, China (2015-2019).

Lanzhou is the largest heavy industrial city in northwest China and it is a typical geographical valley-like city. However, there are few studies on the relationship between air pollutants and COPD, and their respective sample sizes are small, resulting in inconsistent results. The aim of this study is to analyze the effects of air pollutants on COPD hospitalizations in Lanzhou, China. An ecological time series study with distributed lag non-linear model (DLNM) was used for analysis. Daily COPD hospitalization data in Lanzhou from 1 January 2015 to 31 December 2019 were collected from 25 hospitals, as well as air pollutant data and meteorological data. A total of 18,275 COPD hospitalizations were enrolled. For 10 μg/m3 increase in PM2.5, PM10, SO2, NO2, and 1 mg/m3 increase in CO at lag 07 day, the RR95%CI of COPD hospitalizations were 1.048 (1.030, 1.067), 1.008 (1.004, 1.013), 1.091 (1.048, 1.135), 1.043 (1.018, 1.068), and 1.160 (1.084, 1.242), respectively. The exposure-response curves between air pollutants (except O3-8h) and COPD hospitalizations were approximately linear with no thresholds. Female, and the harmful effect of PM on aged <65 years, the effect of gaseous pollutant on those aged ≥65 years, were stronger, particularly in the cold season. Exposure to air pollutants (except O3-8h) might increase the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD. Exposure to air pollutants (except O3-8h) increases the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD hospital admissions. The harmful effect of gaseous pollutants (except O3-8h) on COPD-hospitalized patients was stronger than that of PM.

Air pollution and firms' export product quality: Evidence from China

AbstractThis study provides causal estimates of the effect of air pollution on firms' export product quality, based on China's experience. Using thermal inversions as an instrument, a 1% increase in PM2.5 is associated with a 0.25% decrease in export product quality. A series of tests indicates the robustness of our main result. Heterogeneity analysis reveals that the negative impact of air pollution on export product quality is only significant among regions with high levels of air pollution. In addition, we find that air pollution also reduces firms' export sales, share and probability. Our study provides original evidence for the relationship between air pollution and firms' export product quality, offering a unique perspective for countries to enhance export competitiveness.

Interpregnancy interval, air pollution, and the risk of low birth weight: a retrospective study in China

BackgroundBoth interpregnancy intervals (IPI) and environmental factors might contribute to low birth weight (LBW). However, the extent to which air pollution influences the effect of IPIs on LBW remains unclear. We aimed to investigate whether IPI and air pollution jointly affect LBW.MethodsA retrospective cohort study was designed in this study. The data of birth records was collected from the Jiangsu Maternal Child Information System, covering January 2020 to June 2021 in Nantong city, China. IPI was defined as the duration between the delivery date for last live birth and date of LMP for the subsequent birth. The maternal exposure to ambient air pollutants during pregnancy—including particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5), PM10, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)—was estimated using a hybrid kriging-LUR-RF model. A novel air pollution score was proposed, assessing combined exposure to five pollutants (excluding CO) by summing their concentrations, weighted by LBW regression coefficients. Multivariate logistic regression models were used to estimate the effects of IPI, air pollution and their interactions on LBW. Relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (S) were utilized to assess the additive interaction.ResultsAmong 10, 512 singleton live births, the LBW rate was 3.7%. The IPI-LBW risk curve exhibited an L-shaped pattern. The odds ratios (ORs) for LBW for each interquartile range increase in PM2.5, PM10, O3 and the air pollution score were 1.16 (95% CI: 1.01–1.32), 1.30 (1.06–1.59), 1.22 (1.06–1.41), and 1.32 (1.10–1.60) during the entire pregnancy, respectively. An additive interaction between IPI and PM2.5 was noted during the first trimester. Compared to records with normal IPI and low PM2.5 exposure, those with short IPI and high PM2.5 exposure had the highest risk of LBW (relative risk = 3.53, 95% CI: 1.85–6.49, first trimester).ConclusionThe study demonstrates a synergistic effect of interpregnancy interval and air pollution on LBW, indicating that rational birth spacing and air pollution control can jointly improve LBW outcomes.

Association between long-term exposure to low ambient PM2.5 and cardiovascular hospital admissions: A UK Biobank study

IntroductionA causal link between air pollution exposure and cardiovascular events has been suggested. However fewer studies have investigated the shape of the associations at low levels of air pollution and identified the most important temporal window of exposure. Here we assessed long-term associations between particulate matter < 2.5 µm (PM2.5) at low concentrations and multiple cardiovascular endpoints using the UK Biobank cohort. MethodsUsing data on adults (aged > 40) from the UK Biobank cohort, we investigated the associations between 1-year, 3-year and 5-year time-varying averages of PM2.5 and incidence of major adverse cardiovascular events (MACE), myocardial infarction (MI), heart failure, atrial fibrillation and flutter and cardiac arrest. We also investigated outcome subtypes for MI and stroke. Events were defined as hospital inpatient admissions. We fitted Cox proportional hazard regression models applying extensive control for confounding at both individual and area level. Finally, we assessed the shape of the exposure–response functions to assess effects at low levels of exposure. ResultsWe analysed data from 377,736 study participants after exclusion of prevalent subjects. The average follow-up (2006–2021) was 12.9 years. We detected 19,353 cases of MACE, 6,562 of acute MI, 6,278 of heart failure, 1,258 for atrial fibrillation and flutter, and 16,327 for cardiac arrest. Using a 5-year exposure window, we detected positive associations (for 5 μg/m3 increase in PM2.5) for 5-point MACE of [1.12 (95 %CI: 1.00–1.26)], heart failure [1.22 (1.00–1.50)] and cardiac arrest [1.16 (1.03–1.31)]. We did not find any association with acute MI, while non-ST-elevation MI was associated with the 1-year exposure window [1.52 (1.12–2.07)]. The assessment of the shape of the exposure–response relationships suggested that risk is approximately linear for most of the outcomes. ConclusionsWe found positive associations between long-term exposure to PM2.5 and multiple cardiovascular outcomes for different exposure windows. The cardiovascular risk tends to rise even at exposure concentrations below 12–15 μg/m3, indicating high risk below UK national and international thresholds.